{
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  {
   "cell_type": "markdown",
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   "source": [
    "# Operations on a Computational Graph\n",
    "\n",
    "We start by loading the necessary libraries and resetting the computational graph."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
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   "source": [
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "from tensorflow.python.framework import ops\n",
    "ops.reset_default_graph()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Start a graph session"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "sess = tf.Session()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Create tensors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
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   "outputs": [],
   "source": [
    "# Create data to feed in the placeholder\n",
    "x_vals = np.array([1., 3., 5., 7., 9.])\n",
    "\n",
    "# Create the TensorFlow Placceholder\n",
    "x_data = tf.placeholder(tf.float32)\n",
    "\n",
    "# Constant for multilication\n",
    "m = tf.constant(3.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "We loop through the input values and print out the multiplication operation for each input."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.0\n",
      "9.0\n",
      "15.0\n",
      "21.0\n",
      "27.0\n"
     ]
    }
   ],
   "source": [
    "# Multiplication\n",
    "prod = tf.multiply(x_data, m)\n",
    "for x_val in x_vals:\n",
    "    print(sess.run(prod, feed_dict={x_data: x_val}))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Output graph to Tensorboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "merged = tf.summary.merge_all(key='summaries')\n",
    "if not os.path.exists('tensorboard_logs/'):\n",
    "    os.makedirs('tensorboard_logs/')\n",
    "\n",
    "my_writer = tf.summary.FileWriter('tensorboard_logs/', sess.graph)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "![Operations on a Graph](https://github.com/nfmcclure/tensorflow_cookbook/raw/master/02_TensorFlow_Way/images/01_Operations_on_a_Graph.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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   "source": []
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